Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

O'Reilly on Data

MAY 18, 2020

All predictive models are wrong at times?—just As the renowned statistician George Box once quipped , “All models are wrong, but some are useful.” Broadly speaking, materiality is the product of the impact of a model error times the probability of that error occuring. just hopefully less so than humans.

Risk 357

Risk Modeling Data Processing Software 357

Birst BI

MAY 29, 2018

Today, BI vendors are already introducing AI capabilities in their products for data preparation, data discovery, and data science. Data from multiple sources was normally stored in silos, and research was typically presented in a fragmented, disjointed report that was open to interpretation.

Slice and Dice 74

Slice and Dice Analytics Business Intelligence Machine Learning 74

Insight

AUGUST 5, 2020

Photo by Devon Divine on Unsplash Originally published in Maslo - Your Virtual Self. This created a summary features matrix of 7472 recordings x 176 summary features, which was used for training emotion label prediction models. To prevent data-leakage issues, actors in the training dataset did not reappear in the test datasets.

Predictive Modeling 98

Predictive Modeling Statistics Modeling Measurement 98

O'Reilly on Data

SEPTEMBER 19, 2023

While data scientists were no longer handling Hadoop-sized workloads, they were trying to build predictive models on a different kind of “large” dataset: so-called “unstructured data.” You can see a simulation as a temporary, synthetic environment in which to test an idea. And it was good.

Machine Learning 243

Machine Learning Testing Modeling Cost-Benefit 243

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. A single model may also not shed light on the uncertainty range we actually face. Over the life of the forecast, the data scientist will publish historical accuracy metrics.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Domino Data Lab

NOVEMBER 17, 2020

Our previous Domino Blog on the Curse of Dimensionality [2] , describes weird behaviors that emerge in data when P >> N: Points move far away from each other. Points fall on the outer edges of the data distribution. Predictive models fit to noise approach 100% accuracy. The 12 are listed in Table 1. Antimicrobial.

Statistics 131

Statistics Measurement Testing Predictive Modeling 131